Systems and methods for generating electronic map displays with points-of-interest based on density thresholds

ABSTRACT

Methods and systems are provided for generating an electronic map display. In one implementation, a method is provided for determining a route distance based on information for a route, comparing the route distance with a distance threshold, defining a search area when the route distance is less than the distance threshold, the search area including boundaries, calculating, using a processor, a points of interest (POI) density of the search area, comparing the POI density with a first density threshold and a second density threshold, adjusting the boundaries of the search area based on a result of comparing the POI density with the first density threshold and the second density threshold, identifying POIs in the adjusted search area, and providing POI information for an electronic map display, the POI information being associated with one or more POIs identified in the adjusted search area.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit ofpriority to, U.S. patent application Ser. No. 14/178,225, filed on Feb.11, 2014 (now allowed), which is a continuation of U.S. patentapplication Ser. No. 13/019,646, filed on Feb. 2, 2011 (now U.S. Pat.No. 8,681,022). The above applications are incorporated herein byreference to their entireties.

BACKGROUND

Technical Field

The present disclosure generally relates to the field of computerprocessing and electronic map displays. More particularly, and withoutlimitation, the present disclosure relates to computerized systems andmethods for generating electronic map displays based on, for example,points-of-interest (POI) density, route distance, and/or distances ofPOIs from reference locations.

Background Information

Today, electronic map displays are widely used to convey informationabout roads, traffic, buildings, landmarks, terrain, etc., related togeographical regions of interest. Interactive maps may allow a user, forexample, to access a map of a particular location (e.g., specificaddress, city, state, country, etc.) and the surrounding locations.After accessing a location, a user may navigate around the location byzooming in and out, and scrolling left, right, up, and down on the map.A user may also use the map to retrieve directions/routes between two ormore locations. Because of their versatility, electronic map displaysare used in a variety of different computer systems and applications.For example, electronic map displays are used in personal navigationdevices to convey driving and/or walking directions to the user. Inaddition, electronic map interfaces are available from a variety ofInternet resources (e.g., www.mapquest.com) for use by the public.

Interactive maps may also provide information about various POIs near alocation selected or specified by a user. A POI may be, for example, aspecific entity or attraction that is useful or interesting to anindividual or a group of individuals, or that the individual or thegroup may want to visit. By way of example, POIs on a map display mayrepresent gas stations, rest areas, hotels, restaurants, museums,hospitals, historical sites in a specific geographic area, houses forsale, etc. A POI may also correspond to a movie theater showing aparticular film, a restaurant that serves a specific type of food, suchas pizza, etc.

A user may search for specific POIs that the user wants to locate byentering information for a query. Search results for identified POIs maybe provided to a user based on the query. The search results may bewithin either search boundaries set by an arbitrary radius (e.g., 1mile, 5 miles, 10 miles, etc.) from a location, a geographic region(e.g., neighborhood, city, etc.) defined by a polygon, or an arbitrarypolygon (e.g., square, etc.) surrounding a location. As a result, POIsthat are outside a search boundary are not provided to the user. Inaddition, a user is denied the opportunity to consider POIs that mightbetter fit the user's preferences based on the query and/or based on theroute on which the user is driving. At the same time, when a userexpands the geographic scope of search results, a user is often providedwith an electronic map display that is crowded with too many POIs thatare unappealing to the user.

Further, as the number of POIs represented increases, electronic mapdisplays may become cluttered and difficult to read. For example, if auser searches for “pizza” in New York City, the number of POI iconsshown on the map display may be quite large, rendering the map displayunwieldy and difficult to read. At the same time, some POI icons mayoverlap one another, hiding some information that may be of interest tothe user. In contrast, when searching for POIs within rural areas oralong routes of great distance, conventional map displays may determinethat no POIs are available within the search boundaries and/or maydisplay POIs that may require the user to take a long detour away fromthe route, causing inconvenience to the user.

In view of the foregoing, there is a need for improved techniques forgenerating electronic map displays. Preferably, such techniques shouldbe more efficient, while also providing relevant or useful searchresults in comparison to that provided by conventional methods.Moreover, there is a need for improved methods and systems for providingsearch results of relevant POIs in response to a query from a user thatare not necessarily limited to search boundaries and account for POIdensity, the distance of the route, and distances of POIs from referencelocations along the route.

SUMMARY

Consistent with the present disclosure, computerized systems and methodsare provided for generating electronic map displays for users.Embodiments of the present disclosure are also provided for identifyingand presenting electronic map displays with POI information. Moreover,in accordance with certain embodiments, computerized systems and methodsare provided for generating electronic map displays based on, forexample, POI density, route distance, and/or distances of POIs fromreference locations.

In accordance with one exemplary embodiment, a computer-implementedmethod for generating an electronic map display is provided. The methodcomprises determining a route distance based on information for a route;comparing the route distance with a distance threshold; defining asearch area when the route distance is less than the distance threshold,the search area including boundaries; calculating, using a processor, apoints of interest (POI) density of the search area; comparing the POIdensity with a first density threshold and a second density threshold;adjusting the boundaries of the search area based on a result ofcomparing the POI density with the first density threshold and thesecond density threshold; identifying POIs in the adjusted search area;and providing POI information for an electronic map display, the POIinformation being associated with one or more POIs identified in theadjusted search area.

In accordance with another exemplary embodiment, a system for generatingan electronic map display is provided. The system comprises an inputdevice for receiving input from a user; a display device for displayingthe electronic map display; a processor configured to determine a routedistance based on information for a route, compare the route distancewith a distance threshold, define a search area when the route distanceis less than the distance threshold, the search area includingboundaries, calculate a points of interest (POI) density of the searcharea, compare the POI density with a first density threshold and asecond density threshold, adjust the boundaries of the search area basedon a result of comparing the POI density with the first densitythreshold and the second density threshold, identify POIs in theadjusted search area, and provide POI information for an electronic mapdisplay, the POI information being associated with one or more POIsidentified in the adjusted search area

Consistent with another exemplary embodiment, there is provided acomputer-readable storage medium storing a program, which, when executedby a computer, causes the computer to perform a method for generating anelectronic map display. The method comprises determining a routedistance based on information for a route; comparing the route distancewith a distance threshold; defining a search area when the routedistance is less than the distance threshold, the search area includingboundaries; calculating a points of interest (POI) density of the searcharea; comparing the POI density with a first density threshold and asecond density threshold; adjusting the boundaries of the search areabased on a result of comparing the POI density with the first densitythreshold and the second density threshold; identifying POIs in theadjusted search area; and providing POI information for an electronicmap display, the POI information being associated with one or more POIsidentified in the adjusted search area.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory only,and should not be considered restrictive of the scope of the invention,as described and claimed. Further, features and/or variations may beprovided in addition to those set forth herein. For example, embodimentsof the invention may be directed to various combinations andsub-combinations of the features described in the detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a representation of an exemplary system for generating andproviding electronic maps, consistent with embodiments of the presentdisclosure;

FIG. 2 is a representation of the components and information that maystored or otherwise associated with a client, consistent withembodiments of the present disclosure;

FIG. 3 is a representation of the components and information that may bestore or otherwise associated with a server, consistent with embodimentsof the present disclosure;

FIG. 4 is a flowchart depicting an exemplary method for generating anelectronic map display, consistent with embodiments of the presentdisclosure;

FIG. 5 is a flowchart depicting an exemplary method for determining aPOI based on a reference point, consistent with embodiments of thepresent disclosure;

FIG. 6 is a flowchart depicting an exemplary method for determining aPOI based on a route distance and POI density of locations along aroute, consistent with embodiments of the present disclosure;

FIG. 7 is a flowchart depicting an exemplary method for adjusting searchareas to determine a POI based on POI density of locations along theroute, consistent with embodiments of the present disclosure;

FIG. 8 is a representation of an exemplary electronic map displayincluding POIs based on a reference point, consistent with embodimentsof the present disclosure; and

FIG. 9 is a representation of an exemplary electronic map displayincluding POIs based on an adjusted search area and POI density,consistent with embodiments of the present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments of thedisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

FIG. 1 is a representation of an exemplary electronic map system 100,consistent with embodiments of the present disclosure. As shown in FIG.1, electronic map system 100 may include a client 102 and a server 104connected via a network 106. Although only one client 102 and one server104 are illustrated in FIG. 1, it will be appreciated that othercomponents may be included in system 100, including a plurality ofclients 102 and a plurality of servers 104, which communicate vianetwork 106, alone and/or in combination with other networks.

By way of example, client 102 may comprise a personal computer (PC), ahand-held computer, a personal digital assistant (PDA), a portablenavigation device, a mobile phone, and/or any other computing deviceknown in the art. Client 102 may include a processor 108, a memory 110,one or more input/output (I/O) devices 112, and a network interface 114for communicating with other components via network 106.

Processor 108 may comprise one or more processors (e.g., a CPU)configured to execute instructions and to process data to perform one ormore functions associated with electronic map system 100. For example,processor 108 may be configured to execute instructions to perform theexemplary methods or steps disclosed herein.

Memory 110 may comprise one or more memory devices that store data, suchas, for example, random access memory (RAM), read-only memory (ROM), amagnetic storage device (e.g., a hard disk), an optical storage device(e.g., a CD- or DVD-ROM), an electronic storage device (e.g., EPROM or aflash drive), and/or any other data storage device known in the art.Memory 110 may store one or more applications for performing theexemplary methods or steps disclosed herein. Consistent with the presentdisclosure, the applications may be implemented using applets, plug-ins,modules, and/or any other suitable software components or set ofinstructions.

FIG. 2 illustrates exemplary components and information that may bestored in client memory 110 or otherwise associated with client 102,consistent with embodiments of the present disclosure. As shown in theexample of FIG. 2, memory 110 may store an operating system 200, such asDOS, Windows, or Linux. Memory 110 may also include one or moreapplication programs 202, such as word processing, database programs,spreadsheet programs, presentation programs, graphics programs, and/orother programs capable of generating documents or other electroniccontent. Memory 110 may also include browser applications 204 capable ofrendering standard Internet content, such as Netscape Navigator,Microsoft Internet Explorer, Mozilla Firefox, and/or Safari. Processor108 may leverage and execute operating system 200, application programs202, and/or browser applications 204, including to support the exemplarymethods or steps disclosed herein.

Referring back to FIG. 1, I/O devices 112 may include one or morecomponents allowing a user of electronic map system 100 to interfacewith a plurality of clients, including client 102. For example, I/Odevices 112 may include user input devices, such as a keyboard, akeypad, a mouse, a touch pad, a touch screen, a microphone, anaccelerometer, and/or any other user input device known in the art. I/Odevices 112 may also include output devices such as a display (e.g., anLCD, a CRT display, or a plasma display), a printer, a speaker, and/orany other suitable output device.

Network interface 114 may comprise any communication device for sendingand receiving data. For example, network interface 114 may include amodem, a transceiver, a set-top box, a network communication card, asatellite dish, an antenna, and/or any other network adapter capable oftransmitting and receiving data over network 106.

Server 104 may comprise a PC, a mainframe computer, and/or any othercomputing device known in the art. Similar to client 102, server 104 mayinclude a processor 116, a memory 118, one or more I/O devices 120,and/or a network interface 122 for communicating with other componentsvia network 106. As will be appreciated from this disclosure, one ormore components of server 104 may be the same or similar to thosediscussed above in connection with client 102 and, accordingly,discussion thereof is omitted. Server 104 may respond to a request fromclient 102 received from network 106 in connection with the exemplarymethods or steps disclosed herein.

Consistent with certain embodiments, server 104 may comprise a singleserver computer or a collection of server computers, alone or incombination with other components, such as a global positioning system(GPS) (not shown). For example, server 104 may be part of a distributedserver network (not shown) and may distribute data for parallelprocessing to one or more additional servers on the distributed servernetwork. As a further example, server 104 comprises a server farmincluding a plurality of server computers and a load balancer forprocessing communications and handling requests from a plurality ofclients.

FIG. 3 illustrates exemplary components and information that may bestored in server memory 118 or otherwise associated with server 104,consistent with embodiments of the present disclosure. As shown in FIG.3, memory 118 may include an operating system 300, a map application302, a map database 304, a POI database 306, and a routing engine 308.

Map application 302 may comprise one or more electronic mappingapplications configured to render map displays based on stored map dataand user input. Map database 304 may contain cartographic information,geographic information, road information, satellite image information,traffic information, maneuver lists, and/or other information about oneor more geographical regions of interest. POI database 306 may containaddress information, latitude/longitude information, ID numbers, websiteaddresses, descriptive information, and/or other information aboutvarious POIs within the geographical regions of interest. POI database306 may also include optimization criteria that may be used to locatePOIs and/or POI information. The optimization criteria may include userpreferences, predetermined thresholds, density parameters, referencelocations, and/or other information that may be used to provide POIsand/or POI information based on relevant factors such as distance of aspecific route, POI density within a particular search region, and/orrelative distances of POIs from a reference location.

Routing engine 308 may be used to generate routes, to perform analysison segments of generated routes, and/or to provide a user withinformation corresponding to POIs along a particular route. For example,routing engine 308 may request map application 302 to provide relevantinformation from map database 304 and POI database 306 to generate aparticular route. Alternatively, or additionally, routing engine 308 mayretrieve the relevant information directly from map database 304 and/orPOI database 306. Processor 116 may leverage and execute operatingsystem 300, map application 302, map database 304, POI database 306,and/or routing engine 308 in connection with, for example, the methodsand steps disclosed herein.

FIG. 4 is a flowchart depicting an exemplary method 400 for generatingan electronic map display, consistent with embodiments of the presentdisclosure. Method 400 may be performed based on, for example, programmodules stored in client memory 110 and/or server memory 118. Althoughmethod 400 is described below as being performed by server 104, it is tobe appreciated that method 400 may be performed by server 104 and client102, either individually or in combination. For example, client 102 mayperform method 400 based on data provided by server 104, or server 104may perform method 400 based on data provided by client 102.Alternatively, client 102 and server 104 may each perform differentportions of method 400.

Referring to FIG. 4, in step 402, server 104 may receive input data fromclient 102. The input data may be entered by a user and may include arequest for a map of a particular location, a request for a POI, arequest for generating a route between an origination point and adestination point, a request for providing driving directions, a requestfor providing walking directions, and/or other requests associated withelectronic map displays or information. For example, a user at client102 may access a mapping application associated with server 104 byentering a domain name or uniform resource locator (URL) into a webbrowser application (e.g., www.mapquest.com). The user may then provideinput data to request map information for a particular geographicalregion of interest by entering input data, such as a city name, anaddress, or other information, into the mapping application as a searchkey. Alternatively, or additionally, the user may request mapinformation for a particular geographical region of interest byproviding input directly to a map interface associated with the mappingapplication (e.g., zooming, panning, etc.).

In step 404, server 104 may receive map information to process therequest based on the input data received in step 402. Map application302 may retrieve relevant map information from, for example, mapdatabase 304. Next, in step 406, it is determined whether the input datareceived in step 402 includes a request for calculation of a route. Themethod proceeds to step 408 when calculation of a route is not requested(step 406: No) and a map display may be provided based on the mapinformation. The map display may be provided to client 102 via network106 and may also include graphical icons representing POIs within themap. The graphical icons (not shown) may be generated by map application302 based on POI information retrieved from POI database 306. Client 102and/or server 104 may display the map information as a map view or aportion of an overall map that is displayed and viewable to the user.

Alternatively, the method may proceed to step 410 when calculation of aroute is requested (step 406: Yes) and a route may be calculated basedon map information received in step 402. The route may be calculated byrouting engine 308 and/or map application 302. In step 412, it isdetermined whether input data includes a request for POIs along theroute. Alternatively, the request for POIs along the requested route maybe received after generation of the route or triggered automatically.

The method proceeds to step 414 when a POI request is not received (step412: No) and route information corresponding to the calculated route isprovided. The route information may be provided to client 102 vianetwork 106 and may include a map display, turn-by-turn directions,instructions to generate audio and/or graphical output as the usertraverses through the calculated route, advertisement informationassociated with POIs along the route, and/or other information. Theroute information may include a combination of text and graphics that isdisplayed and viewable to the user. Further, depending on a preferenceof a user included in POI database 306, routing engine 308 may refineand/or format the route information before providing it to client 102.For example, POI database 306 may indicate that a particular user ishearing impaired and/or may have additional disabilities that mayrequire the routing instructions to be delivered in a specific formatgoverned by regulations and/or other technological limitations of auser's device. As is indicated in FIG. 4, steps 412 and 414 may beoptional and process 400 may move directly from step 410 to 416, suchthat POI information may be automatically provided with routeinformation without determining whether a POI request was received.

Alternatively, the method may proceed to step 416 when a request for aPOI is received (step 412: Yes) and server 104 may receive POIinformation for locations along the route. For example, the user mayenter a search key (e.g., “Holiday Inn,” “pizza,” etc.) into a searchinterface provided by the mapping application. Map application 302 maythen search POI database 306 based on the search key and may retrievePOI information (e.g., latitude and longitude information, name,address, icon graphic information, etc.) corresponding to each of thePOIs identified by the search that are located along the calculatedroute. Map application 302 may provide the POI information to routingengine 308 for determination of a suitable POI along the calculatedroute.

Next, in step 418, optimization criteria may be received. Theoptimization criteria may be retrieved from POI database 306 by mapapplication 302 and may be provided to routing engine 308 or may beretrieved directly by routing engine 308. The optimization criteria mayinclude user preferences, predetermined thresholds, density parameters,reference locations, and/or other information that may be used toprovide suitable POIs based on relevant factors such as distance of thecalculated route, POI density within a particular search region alongthe calculated route, and/or relative distances of POIs from a referencelocation along the calculated route.

In step 420, locations of one or more POIs may be determined based onthe calculated route, the POI information, and/or the optimizationcriteria. As will be explained in detail below with respect to FIGS.5-7, routing engine 308 may perform various processing tasks todetermine locations of POIs along a calculated route. For example,routing engine 308 may divide the calculated route into segments ofequal or varying distances and may calculate a POI density for eachsegment. Routing engine 308 may compare the POI density with a thresholddensity and, depending on a result of the comparison, may increase ordecrease the search radius along a particular segment to search for aPOI. In addition, after dividing the calculated route into segments ofequal or varying distances, routing engine 308 may search for groups ofPOIs for each segment and may determine the density of each group toprovide the user with a location having, for example, multiple POIs inclose proximity to each other along the route. Further, routing engine308 may determine reference points along the route, such as rest areasand/or exits along an interstate, and search for POIs nearest to thereference points.

Next, in step 422, route information and POI information may be providedand processing may end. As part of this step, a electronic map displaymay be generated that includes the POI information. In accordance withone embodiment, server 104 may provide route information and POIinformation to client 102 via network 106, whereby the information isprovided as part of control signals or instructions for rendering anelectronic map display. Server 104 may also provide client 102 with, forexample, turn-by-turn directions, instructions to generate audio and/orgraphical output as the user traverses through the calculated route,advertisement information associated with POIs along the route,locations of POIs along the route, distances of POIs from referencepoints along the route, ranks of POIs based on matches with searchcriteria and user preferences, and/or other suitable information. Theroute information and POI information may include a combination of textand graphics that is displayed and viewable to the user. Further, asexplained above, routing engine 308 may refine and/or format the routeinformation and POI information before providing it to client 102.

FIG. 5 is a flowchart depicting an exemplary method 500 for determininga POI based on a reference point, consistent with embodiments of thepresent disclosure. As will be appreciated, the exemplary method 500 maybe implemented as part of step 420 of method 400 (FIG. 4). Initially, instep 502, server 104 may determine locations of reference points along acalculated route. The reference points may be determined by routingengine 308 based on information retrieved from map database 304 and/orPOI database 306. By way of example, the reference points may correspondto exits along an interstate, highway, freeway, and/or similar roadway.Reference points may also correspond to rest areas along a calculatedroute, any location manually identified by a user, and/or shape pointsincluded in the route. Shape points may correspond to maneuver pointsincluded in a maneuver list, stored in map database 304, that provides alist of predetermined location points where a vehicle is instructed toproceed in a certain direction along the calculate route. Each shapepoint includes a latitudinal and longitudinal value identifying itslocation with respect to its physical location on the surface of theearth. The number of shape points and the position of shape points maydetermine the geographic condition of the path being navigated.

In step 504, a spatial identifier may be assigned to each referencepoint. To define spatial identifiers, routing engine 308 may firstdetermine a latitude and a longitude of a particular reference point andmay determine the significance of the reference point. For example, anentity such as “Grand Canyon” may have a high (global) significance, anda local gas station may have a low (localized) significance. A highsignificance may mean that the reference point should be identified on awide geographic scope, and a low significance may mean that thereference point has a localized scope.

Next, in step 506, a search area may be defined for each spatialidentifier identified in step 504. The search area may be defined byrouting engine 308 and may correspond to a polygon whose boundaries aredrawn around a reference point. A polygon with large boundaries may bedefined to search for a POI around a reference point having a spatialidentifier with high significance, and a polygon with smaller boundariesmay be defined to search for a POI around a reference point having aspatial identifier with low significance.

In step 508, a search may be conducted for POIs within the search areasassociated with the spatial identifiers. In step 508, the search areamay be increased or decreased when a high number of POIs or no POIs arefound within the search areas associated with the spatial identifiers.Further, and as will be explained below with reference to the example ofFIG. 6, the search area may be adjusted based on a comparison between adensity of a particular search area with a predetermined densitythreshold.

Next, in step 510, distances of POIs found in step 508 may be calculatedfrom corresponding reference points, and the POIs may be ranked andsorted to provide suitable POI information (step 512). The distances ofPOIs may be calculated by routing engine 308 and/or map application 302by using map information and POI information retrieved from map database304 and POI database 306, respectively.

Routing engine 308 may rank and sort the POIs associated with each areabased on a plurality of factors that may be assigned different weightsto calculate the ranks. For example, a POI may be determined to be themost suitable POI and may be assigned the highest rank when the distancebetween it and the reference point is shortest compared to distancesbetween the reference point and other POIs. Further, a POI may bedetermined to be the most suitable POI and may be assigned the highestrank when the driving duration between it and the reference point isdetermined to be smallest compared to durations between the referencepoint and other POIs. Additional factors may include one or more of thelevels of matches with the search criteria provided by a user,preferences of users included in optimization criteria, quality of POIsthat may be determined based on information gathered from public sources(e.g., quality of restaurant, cleanliness of rest area, pet friendlylocation, healthy food options, or price of gas), types of POIsrequested by a user, and/or any other relevant factors.

FIG. 6 is a flowchart depicting an exemplary method 600 for determininga suitable POI based on route distance and POI density of locationsalong the route, consistent with embodiments of the present disclosure.As will be appreciated, the exemplary method 600 may be implemented aspart of step 420 of method 400 (FIG. 4). Initially, in step 602, server104 may determine a total distance of the route calculated in step 410of method 400. The route distance may be calculated by routing engine308 based on map information retrieved from map database 304. In step604, it may be determined whether the route distance is greater than orequal to a distance threshold. The distance threshold may be apredetermined value retrieved from optimization criteria and/or may be avalue that is dynamically generated by routing engine 308 or manuallyprovided by a user. For example, I/O devices 120 of server 104 maydisplay a screen including clickable options and/or prompt a user toselect whether the route distance should be used as a factor todetermine the location of POIs.

The method proceeds to step 606, when the route distance is not greaterthan or equal to the distance threshold (step 604: No), and a list ofPOIs along the route is generated. The list of POIs may be generated byrouting engine 308 based on POI information received from POI database306 in step 416 of method 400 and/or may be dynamically generated byperforming real-time searches. The distance threshold may be retrievedfrom optimization criteria or may be generated dynamically. In step 608,reference points and/or search areas may be defined along the route. Thereference points and/or search areas may be defined by using the same orsimilar processes as described above with respect to method 500. Next,in step 610, the list of POIs may be used to generate various groups orbuckets of POIs. All POIs that are determined to be located within aparticular search area may be grouped together and placed in a singlebucket. Alternatively, or additionally, all POIs that are at apredetermined distance from a reference point and/or at a predetermineddistance from each other may be grouped together and placed in a singlebucket. The predetermined distance may be retrieved from optimizationcriteria.

In step 612, POI density of each POI group or bucket may be calculated.The POI density may be calculated by determining the number of POIs ineach group or bucket, and/or other factors such as the proximity of thePOIs in a group from each other and/or the distance of the POIs in agroup from a reference point. In step 614, the groups or buckets of POIsmay be ranked based on various factors. For example, the density of eachPOI bucket may be compared to a density threshold and the POI buckethaving the highest differential may be ranked the highest. Further, thePOI bucket having the greatest number of POIs of a particular type orcategory may be ranked the highest. For example, if the user issearching for restaurants, the POI bucket having the highest number ofrestaurants may be ranked the highest. Additional factors, such assafety of the location, reviews of POIs retrieved from public sources,service area time of restaurants, diversity of POIs (e.g., repair shops,restaurants, gas stations, shopping malls, and other commerciallocations) within one group, accessibility from major freeways, trafficconditions, and/or other suitable factors, may be used to rank thegroups or buckets.

In addition, user criteria and/or a predetermined threshold may be usedto limit further consideration of POI buckets. For example, whenmultiple POI buckets are highly ranked in step 614, routing engine 308may select only the top three or four ranked POI buckets for furtherprocessing and may disregard the remaining POI buckets. A cut-off levelfor POI buckets may be used based on user criteria and/or apredetermined threshold. Similarly, a high number of POI buckets havingPOIs of a particular type may be displayed along with a low number ofPOI buckets having POIs of a different type. For example, if a usersearched for Italian food, routing engine 308 may determine that ten POIbuckets have a rank that have a POI density greater than densitythreshold. Out of the ten POI buckets, there may be four POI bucketsthat may include multiple Italian restaurants, while there may be twoPOI buckets that may include restaurants that do not serve Italian food.Routing engine 308 may select three out of the four POI buckets havingmultiple Italian restaurants and may select one out of the two POIbuckets that include restaurants that do not serve Italian food to limitprocessing time and to provide the user with diverse results.

Next, in step 616, POIs within the ranked groups or buckets may beranked and sorted to provide suitable POI information. Routing engine308 may iterate through the ranked groups in an order based on theranking of the groups. For example, the POIs included in the highestranked group or bucket may be ranked first based on a plurality offactors that may be assigned different weights as explained above withrespect to method 500. Suitable POI information may be provided in asequential order as the POIs are being ranked for each bucket or thesuitable information may be sent after the POIs in all the buckets havebeen ranked. The POIs may be ranked by using similar techniques asdescribed above with respect to the ranking of POI buckets. For example,only a select number of POIs may be displayed that may be less than aselected user criteria and/or a predetermined threshold.

In addition, only a limited number of POIs may be selected based on thesignificance of the type of POI that may have been requested by a user.For example, a user may be searching for a gas station or a hospital,and it may not be important to provide the user with different optionsof gas stations or hospitals. Routing engine 308 may select a POI thatmay correspond to the highest ranked gas station or hospital.Alternatively, if a user is searching for a restaurant, it may beimportant to provide the user with multiple options and routing engine308 may select three POIs that may correspond to the three highestranked restaurants.

Returning now to step 604, the method may proceed to step 618, when theroute distance is greater than or equal to the distance threshold (step604: Yes). In step 618, the route may be divided into segments of equalor varying distances. The route may be divided into smaller segments byrouting engine 308 to allow for quicker processing of data whilesearching for a suitable POI. For example, a user may be driving along aroute of 600 miles and may request a POI at a distance halfway throughthe route. Routing engine 308 would divide the route into 30 segments of20 miles and would start processing POI information corresponding to the20-mile segments near the current location of the route.

Next, in step 620, lists of POIs may be generated for each segmentand/or for the most relevant segment. After the lists of POIs aregenerated for the segments, steps 608 to 616 may be repeated for thesegments. For example, groups or buckets of POIs may be generated forvarious segments and the groups may be ranked to determine the highestranked group in a particular segment. Similarly, POIs within aparticular group in a segment may be ranked to provide suitable POIinformation.

FIG. 7 is a flowchart depicting an exemplary method 700 for adjustingsearch areas to determine a suitable POI based on POI density oflocations along the route, consistent with the disclosed embodiments. Aswill be appreciated, the exemplary method 700 may be implemented as partof step 420 of method 400 (FIG. 4). Initially, in step 702, server 104may determine a total distance of the route calculated in step 410 ofmethod 400. The route distance may be calculated by routing engine 308based on map information retrieved from map database 304. In step 704,it may be determined whether the route distance is greater than or equalto a distance threshold. Step 704 may be performed by using the same orsimilar process performed in step 604 of method 600.

The method proceeds to step 706, when the route distance is not greaterthan or equal to the distance threshold (step 704: No), and a searcharea may be defined along the route. The search area may be defined byusing the same or similar processes as described above with respect tomethod 500 and to perform localized searches to locate POIs along theroute. In step 708, one or more sample points may be determined in thesearch area defined in step 706. The sample points may be determinedbased on similar techniques used to locate reference points in method500. In step 710, the POI density of the defined search area may becalculated based on the sample points. The POI density may be comparedto a first density threshold and a second density threshold (step 712).The first and second density thresholds may be retrieved from theoptimization criteria and/or may be generated dynamically. The firstdensity threshold may represent a sparse area and the second densitythreshold may represent a dense area. For example, a sparse area mayhave very few or no POIs, such as rural South Dakota, and a dense areamay have a high number of POIs, such as Washington, D.C.

In step 714, it is determined whether the POI density falls within thefirst and second density thresholds. The POI density may be determinedto fall within the first and second density thresholds when the POIdensity is greater than the first density threshold and less than thesecond density threshold. The method proceeds to step 716, when the POIdensity does not fall within the range (step 714: No), and the searcharea defined in step 706 may be adjusted based on a result of thecomparison. For example, boundaries of the search area may be increasedwhen the POI density is determined to be less than or equal to the firstdensity threshold. The boundaries are expanded because the comparisonperformed in step 712 may indicate that the defined search area is in asparse area, and a greater area must be searched to provide suitable POIinformation. Further, the boundaries of the search area may be decreasedwhen the POI density is determined to be greater than or equal to thesecond density threshold. The boundaries are decreased because thecomparison performed in step 712 may indicate that the defined searcharea is in a dense area, and a smaller area must be searched to providesuitable POI information.

In step 718, one or more POIs may be located within the adjusted searcharea to provide suitable POI information. Step 718 may include thetechniques described above with respect to methods 500 and 600. Forexample, the POIs may be grouped in buckets and/or may be ranked basedon distances from a reference point.

Alternatively, the method proceeds to step 720, when the POI densityfalls within the range (step 714: Yes), and one or more POIs may belocated within the search area defined in step 706. The POIs are locatedwithin the search area to provide suitable POI information.

Returning now to step 704, the method may proceed to step 722, when theroute distance is greater than or equal to the distance threshold (step704: Yes). In step 722, the route may be divided into segments of equalor varying distances. The route may be divided into smaller segments byrouting engine 308 to allow for quicker processing of data whilesearching for a suitable POI. Next, in step 724, search areas may bedefined for each segment and/or for the most relevant segment of theroute. After the search areas are defined for the segments, steps 708 to720 may be repeated for the segments. For example, POI densities may becalculated for search areas within each segment, and boundaries of thesearch areas may be adjusted based on comparison of the POI densitieswith the first and second density thresholds.

By implementing embodiments of the present disclosure, POIs are locatedand displayed on electronic map displays in a quick and efficientmanner. Further, additional factors, such as POI density of particularareas, route distance, and/or user preferences, may be used to locatePOIs that are most suitable or relevant to the needs of the user.

FIG. 8 is a representation of an exemplary electronic map display 800,consistent with embodiments of the present disclosure. Electronic mapdisplay 800 may be displayed on, for example, input/output (I/O) devices112 of electronic map system 100. Electronic map display 800 may displaya representation of a route 802 and POIs 804 and 806. POI 804 may bedisplayed when, for example, a user requests location informationcorresponding to a POI while the user is traveling along route 802. POI804 may be determined to be a suitable POI as it may be determined to beat a dose distance from reference point 808. Similarly, POI 806 may bedetermined to be a suitable POI as it may be determined to be at a closedistance from reference point 810. POIs 804 and 806 may be located afteradjusting search areas (not shown) along route 802 by, for example,implementing exemplary process 700. Reference points 808 and 810 mayrepresent locations of exits and/or rest areas along route 802 and maynot be included in electronic map display 800.

FIG. 9 is a representation of an exemplary electronic map display 900,consistent with embodiments of the present disclosure. Electronic mapdisplay 900 may be displayed on, for example, input/output (I/O) devices112 of electronic map system 100. Electronic map display 900 may displaya representation of a route 902 and a cluster 904 along route 902.Cluster 904 may be displayed when a user searches for POIs whiletraveling along route 904 and may represent a location having a high POIdensity. For example, as is described above with respect to exemplaryprocess 600, cluster 904 may correspond to a highest ranked group orbucket along route 902. Cluster 904 may include multiple POIs that maymatch a user requested criteria. For example, cluster 904 may includemultiple restaurants serving a particular type of food. Cluster 904 maybe located after adjusting search areas (not shown) along route 902 by,for example, implementing exemplary process 700.

One skilled in the art will appreciate that computer programs forimplementing the disclosure may be stored on and/or read fromcomputer-readable storage media. The computer-readable storage media mayhave stored thereon computer-executable instructions which, whenexecuted by a computer, cause the computer to perform, among otherthings, the processes disclosed herein. Exemplary computer-readablestorage media may include magnetic storage devices, such as a hard disk,a floppy disk, magnetic tape, or any other magnetic storage device knownin the art; optical storage devices, such as CD-ROM, DVD-ROM, or anyother optical storage device known in the art; and/or electronic storagedevices, such as EPROM, a flash drive, or any other integrated circuitstorage device known in the art. The computer-readable storage media maybe embodied by or in one or more components of electronic map system 100(FIG. 1).

One skilled in the art will further realize that the processesillustrated in this description may be implemented in a variety of waysand may include multiple other modules, programs, applications, scripts,processes, threads, or code sections that may all functionallyinterrelate to accomplish the individual tasks described above. Forexample, techniques described in FIG. 5 may be used in combination withtechniques described in FIGS. 6 and 7. Further, it is contemplated thatthese program modules may be implemented using commercially availablesoftware tools, using custom object-oriented code written in the C++programming language, using applets written in the Java programminglanguage, or may be implemented as discrete electrical components or asone or more hard-wired application-specific integrated circuits (ASICs)custom designed for this purpose. In addition, the disclosure may beimplemented in a variety of different data communication networkenvironments and may use software, hardware, or a combination ofhardware and software to provide the disclosed functions.

In the preceding specification, various embodiments have been describedwith reference to the accompanying drawings. It will, however, beevident that various modifications and changes may be made thereto, andadditional embodiments may be implemented, without departing from thebroader scope of the invention as set forth in the claims that follow.The specification and drawings are accordingly to be regarded in anillustrative rather than restrictive sense. It is intended that thespecification and examples be considered as exemplary only, with a truescope and spirit of the invention being indicated by the followingclaims.

What is claimed is:
 1. A computer-implemented method for adjustingsearch areas, the method comprising the following operations performedby at least one processor: determining a route distance based oninformation for a route; comparing the route distance with a distancethreshold; dividing the route into a plurality of segments when theroute distance is greater than or equal to the distance threshold;defining a search area for one of the plurality of segments; calculatinga points of interest (POI) density of the search area; comparing the POIdensity with a first density threshold and a second density threshold;and identifying POIs within boundaries of the search area based on thecomparisons.
 2. The computer-implemented method of claim 1, furthercomprising: adjusting the boundaries of the search area based on thecomparisons; and wherein identifying the POIs within the boundaries ofthe search area based on the comparisons includes identifying POIswithin the adjusted boundaries of the search area.
 3. Thecomputer-implemented method of claim 1, wherein comparing the POIdensity with the first density threshold and the second densitythreshold includes: determining whether the POI density is greater thanthe first density threshold and less than the second density threshold.4. The computer-implemented method of claim 3, further comprising:increasing the boundaries of the search area when it is determined thatthe POI density is less than the first density threshold.
 5. Thecomputer-implemented method of claim 3, further comprising: decreasingthe boundaries of the search area when it is determined that the POIdensity is greater than the second density threshold.
 6. Thecomputer-implemented method of claim 3, wherein identifying the POIswithin the boundaries of the search area based on the comparisonsincludes: identifying the POIs within the boundaries of the search areawhen it is determined that the POI density is greater than the firstdensity threshold and less than the second density threshold.
 7. Thecomputer-implemented method of claim 1, further comprising: providingPOI information for an electronic map, the POI information beingassociated with one or more of the identified POIs.
 8. Thecomputer-implemented method of claim 1, further comprising: determininga location of a sample point within the search area; and calculating thePOI density based on the sample point.
 9. The computer-implementedmethod of claim 1, wherein dividing the route into the plurality ofsegments includes: dividing the route into a plurality of segments ofequal distance.
 10. The computer-implemented method of claim 1, whereindividing the route into the plurality of segments includes: dividing theroute into a plurality of segments of varying distances.
 11. A systemfor adjusting search areas, the system comprising: an input device forreceiving information for a route; a processor configured to: determinea route distance based on the received information for the route;compare the route distance with a distance threshold; divide the routeinto a plurality of segments when the route distance is greater than orequal to the distance threshold; define a search area for one of theplurality of segments; calculate a points of interest (POI) density ofthe search area; compare the POI density with a first density thresholdand a second density threshold; and identify POIs within boundaries ofthe search area based on the comparisons.
 12. The system of claim 11,wherein the processor is further configured to: adjust the boundaries ofthe search area based on the comparisons; and identify POIs within theadjusted boundaries of the search area.
 13. The system of claim 11,wherein comparing the POI density with the first density threshold andthe second density threshold includes: determining whether the POIdensity is greater than the first density threshold and less than thesecond density threshold.
 14. The system of claim 13, wherein theprocessor is further configured to: increase the boundaries of thesearch area when it is determined that the POI density is less than thefirst density threshold.
 15. The system of claim 13, wherein theprocessor is further configured to: decrease the boundaries of thesearch area when it is determined that the POI density is greater thanthe second density threshold.
 16. The system of claim 13, whereinidentifying POIs within the boundaries of the search area based on thecomparisons includes: identifying the POIs within the boundaries of thesearch area when it is determined that the POI density is greater thanthe first density threshold and less than the second density threshold.17. The system of claim 11, wherein the processor is further configuredto: determine a location of a sample point within the search area; andcalculate the POI density based on the sample point.
 18. The system ofclaim 11, wherein dividing the route into the plurality of segmentsincludes: dividing the route into a plurality of segments of equaldistance.
 19. The system of claim 11, wherein dividing the route intothe plurality of segments includes: dividing the route into a pluralityof segments of varying distances.
 20. A non-transitory computer-readablestorage medium storing a program which, when executed by at least oneprocessor, causes the at least one processor to: determine a routedistance based on information for a route; compare the route distancewith a distance threshold; divide the route into a plurality of segmentswhen the route distance is greater than or equal to the distancethreshold; define a search area for one of the segments; calculate apoints of interest (POI) density of the search area; compare the POIdensity with a first density threshold and a second density threshold;and identify POIs within boundaries of the search area based on thecomparisons.